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Statistical analysis of winter orographic precipitation forecasts using a bulk microphysics model

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dc.contributor.authorGaudet, Brian J., author
dc.date.accessioned2022-05-10T16:44:19Z
dc.date.available2022-05-10T16:44:19Z
dc.date.issued1996-06-12
dc.descriptionJune 12, 1996.
dc.descriptionAlso issued as author's thesis (M.S.) -- Colorado State University, 1996.
dc.description.abstractThe Regional Atmospheric Modeling System (RAMS) developed at CSU has been used to generate forecasts in real-time since the 1991-1992 winter season. In the past such forecasts have included a precipitation efficiency parameterization to predict winter precipitation. Such mesoscale model forecasts allow the possibility of predicting the amount of snowpack in remote mountainous regions where observational verification is difficult. However, in case studies the precipitation scheme used with the forecast model tended to greatly underestimate the total amount of precipitation when verified against SNow TELemetry (SNOTEL) automated stations. Since the fall of 1995 the forecast model has had the capability of using the bulk microphysics scheme found in RAMS to produce real-time forecasts of precipitation. In this study one month, April 1995, is chosen for statistical analysis. Each day in the month was simulated with a bulk microphysics version of the forecast model and compared with the actual forecast produced using a 'dump-bucket' precipitation scheme. A variety of statistical analyses are performed to compare the performance of the two models with each other and with observational data, provided from a set of 32 SNOTEL stations and 167 National Weather Service and other climatological data stations. It is shown that in general the microphysics model shows enhanced skill over the other precipitation scheme at the SNOTEL sites, but not at the climatological stations. On average, both models produce similar amounts of total precipitation for the climatological data stations, but the microphysics does a significantly better job at forecasting total precipitation amounts at the higher-elevation SNOTEL stations, though total accumulations are still underestimated. Spatial and meteorological trends in forecasting skill are discussed. Additionally, sensitivity tests, including microphysical simulations using finer grid resolution, are shown, and the results are analyzed.
dc.description.sponsorshipSponsored by Colorado Agricultural Experiment Station COL0692.
dc.format.mediumreports
dc.identifier.urihttps://hdl.handle.net/10217/234963
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relationCatalog record number (MMS ID): 991000234109703361
dc.relationQC852 .C6 no.613
dc.relation.ispartofAtmospheric Science Papers (Blue Books)
dc.relation.ispartofAtmospheric science paper, no. 613
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subject.lcshPrecipitation forecasting
dc.subject.lcshFreezing precipitation -- Forecasting
dc.subject.lcshWinter storms -- Forecasting
dc.titleStatistical analysis of winter orographic precipitation forecasts using a bulk microphysics model
dc.typeText
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